1. Field of the Invention
The present invention relates generally to analyzing physiologic data, and more specifically, to non-invasively assessing sleep pathology and physiology from coherence and/or cross-power measurements.
2. Related Art
At least five percent of the general population suffers from medically significant sleep disorders, the most common being sleep-disordered breathing (also known as sleep apnea). As a major public health concern, sleep disorders contribute to excessive daytime sleepiness and the associated risks of driving accidents, hypertension, heart attacks, strokes, depression, and attention deficit disorders. The prevalence of sleep disorders is much higher (exceeding thirty percent) in select populations such as, individuals having obesity, congestive heart failure, diabetes, and renal failure.
Conventional diagnostic systems for detecting sleep disorders typically involve complex multiple channel recordings in a sleep laboratory and labor intensive scoring, which collectively lead to substantial expense and patient discomfort. An example of a conventional sleep diagnostic system is a full polysomnograph. Polysomnography is the gold standard for detection and quantification of sleep-disordered breathing, and includes sleep staging, scoring of respiratory abnormality (e.g., apneas, hypopneas, flow-limitation, periodic breathing, and desaturation episodes), and limb movements. Typical markers of sleep disorder severity are the sleep fragmentation index, the apnea-hypopnea index, the respiratory disturbance index, an arousal frequency or index, and the oxygen desaturation index.
One of the many limitations of conventional sleep diagnostic systems is the dependence on tedious manual scoring of “events” based on physiologically arbitrary criteria. Only a moderate correlation can be found between these events and cognitive and cardiovascular outcomes. As such, conventional systems leave a significant amount of unexplained variance in effect, and fail to adequately describe the physiologic impact of sleep disorders. Therefore, a quantitative measure that evaluates the impact of sleep disorders on sleep physiology could be useful in clarifying some of the unexplained variance. A continuous biomarker of physiological state may be particularly useful to follow treatment effects. A continuous biomarker may also be useful to discriminate those in whom the seemingly subtle sleep disorder disease is physiologically disruptive. Such physiologically disruptive settings include primary snoring, which, in adults is associated with excessive sleepiness, and in children is associated with inattentive and/or hyperactive behaviors.
Presently, rapid and accurate throughput of sleep diagnostics does not exist, despite the development of limited forms of sleep testing that include various combinations of airflow, respiratory effort, electrocardiogram (ECG), and oximetry. This is especially problematic in conditions such as congestive heart failure and chronic renal failure, where severe and complex forms of sleep apnea may adversely affect both mortality and morbidity. Since conventional sleep studies are so expensive, information on sleep effects are typically limited in the pre-approval assessments of drugs used in neurological and psychiatric practice.
A complementary dimension of assessment in sleep-disordered breathing is the differentiation of obstructive from non-obstructive disease. While the extreme forms of non-obstructive disease are readily identified on standard sleep studies (e.g., central sleep apnea syndrome and Cheyne-Stokes respiration), all degrees of admixture of physiological abnormalities can be seen in clinical practice. Moreover, the physiology can change within the same night based on body position, time of night effects, and sleep stage effects. A method to track physiological switches from obstructive to central pathophysiology that occur spontaneously or are induced by treatment has practical utility, as treatments for these two conditions are different.
Obstructive disease responds well to positive airway pressure, while non-obstructive disease responds poorly to such therapy and may in fact be exaggerated by air pressure. Individuals with certain disease states are at high risk for mixed physiology disorders, including but not restricted to congestive heart failure, chronic renal failure, and post-stroke sleep apnea syndromes. A simple method to assess disease pathophysiology at the diagnostic level can allow modifications of the clinical treatment approach such that therapies that improve central dysfunction may be initiated earlier in the process.
As obstructive disease responds to mechanical therapies (that support the airway) and non-obstructive disease to control-specific approaches (such as, but not limited to, inhalation of oxygen or carbon dioxide), identification of these two types of physiological abnormalities may also allow prognostication of treatment outcomes (prediction of success or failure of therapy).
Therefore, a need exists to develop a technology that can provide a simple, inexpensive, repeatable measure of the presence and impact of a variety of sleep disruptive stimuli (such as noise, pain, drugs, mood disorders, disordered breathing) on sleep state physiology and stability.